The business case for payer support of a community-based health information exchange: a humana pilot evaluating its effectiveness in cost control for plan members seeking emergency department care.

BACKGROUND As emergency department utilization continues to increase, health plans must limit their cost exposure, which may be driven by duplicate testing and a lack of medical history at the point of care. Based on previous studies, health information exchanges (HIEs) can potentially provide health plans with the ability to address this need. OBJECTIVE To assess the effectiveness of a community-based HIE in controlling plan costs arising from emergency department care for a health plan's members. Albert Tzeel. METHODS The study design was observational, with an eligible population (N = 1482) of fully insured plan members who sought emergency department care on at least 2 occasions during the study period, from December 2008 through March 2010. Cost and utilization data, obtained from member claims, were matched to a list of persons utilizing the emergency department where HIE querying could have occurred. Eligible members underwent propensity score matching to create a test group (N = 326) in which the HIE database was queried in all emergency department visits, and a control group (N = 325) in which the HIE database was not queried in any emergency department visit. RESULTS Post-propensity matching analysis showed that the test group achieved an average savings of $29 per emergency department visit compared with the control group. Decreased utilization of imaging procedures and diagnostic tests drove this cost-savings. CONCLUSIONS When clinicians utilize HIE in the care of patients who present to the emergency department, the costs borne by a health plan providing coverage for these patients decrease. Although many factors can play a role in this finding, it is likely that HIEs obviate unnecessary service utilization through provision of historical medical information regarding specific patients at the point of care.

[1]  Rainu Kaushal,et al.  The United Hospital Fund meeting on evaluating health information exchange , 2007, J. Biomed. Informatics.

[2]  T. Eden,et al.  Access to care , 2008, Pediatric blood & cancer.

[3]  C. McDonald,et al.  A randomized, controlled trial of clinical information shared from another institution. , 2002, Annals of emergency medicine.

[4]  D. Rubin,et al.  The central role of the propensity score in observational studies for causal effects , 1983 .

[5]  J. Marc Overhage,et al.  A Framework for evaluating the costs, effort, and value of nationwide health information exchange , 2010, J. Am. Medical Informatics Assoc..

[6]  Cathy Schoen,et al.  How health insurance design affects access to care and costs, by income, in eleven countries. , 2010, Health affairs.

[7]  Joshua R. Vest,et al.  Health information exchange: persistent challenges and new strategies , 2010, J. Am. Medical Informatics Assoc..

[8]  Mark E. Frisse,et al.  Estimated financial savings associated with health information exchange and ambulatory care referral , 2007, J. Biomed. Informatics.

[9]  J. Avorn,et al.  Variable selection for propensity score models. , 2006, American journal of epidemiology.

[10]  Farshad Shirazi,et al.  Efficiency and economic benefits of a payer-based electronic health record in an emergency department. , 2010, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[11]  E. Keeler,et al.  Costs and benefits of health information technology. , 2006, Evidence report/technology assessment.

[12]  K. Grumbach,et al.  Primary care and public emergency department overcrowding. , 1993, American journal of public health.

[13]  J. Gillespie,et al.  Care Coordination for People with Chronic Conditions , 2003 .

[14]  K. S. Lassila,et al.  Assessing the impact of community health information networks: a multisite field study of the Wisconsin Health Information Network. , 1997, Topics in health information management.

[15]  Sarah Thomson,et al.  International profiles of health care systems, 2012 , 2012 .

[16]  Til Stürmer,et al.  A review of the application of propensity score methods yielded increasing use, advantages in specific settings, but not substantially different estimates compared with conventional multivariable methods. , 2006, Journal of clinical epidemiology.

[17]  C. van Walraven,et al.  Population-based study of repeat laboratory testing. , 2003, Clinical chemistry.

[18]  Anne B. Martin,et al.  Recession contributes to slowest annual rate of increase in health spending in five decades. , 2011, Health affairs.

[19]  Peter C Austin,et al.  Propensity score methods gave similar results to traditional regression modeling in observational studies: a systematic review. , 2005, Journal of clinical epidemiology.

[20]  Primer on statistical significance and P values. , 2001, Effective clinical practice : ECP.

[21]  Eric C. Pan,et al.  The value of health care information exchange and interoperability. , 2005, Health affairs.

[22]  A. Kellermann,et al.  Ambulatory visits to hospital emergency departments. Patterns and reasons for use. 24 Hours in the ED Study Group. , 1996, JAMA.